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1. |
Record Nr. |
UNISA990005462960203316 |
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Autore |
AOKI, Masanao |
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Titolo |
Optimal control and system theory in dynamic economic analysis / Masanao Aoki |
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Pubbl/distr/stampa |
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New York, : North Holland, 1976 |
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Materiale a stampa |
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Livello bibliografico |
Monografia |
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2. |
Record Nr. |
UNIORUON00052325 |
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Autore |
ARO, Sanna |
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Titolo |
The heirs of Assyria : Proceedings of the Opening Symposium of the Assyrian and Babylonian Intellectual Heritage Project, held in Tvarminne, October 8-11, 1998 / edited by Sanna Aro and R.M. Whiting |
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Pubbl/distr/stampa |
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Helsinki, : The Neo-Assyrian Text Corpus Project, 2000 |
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ISBN |
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Descrizione fisica |
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XX1, 134 p. : ill. ; 26 cm |
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Altri autori (Persone) |
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ASSIRI - CONFERENZE |
BABILONESI - CONFERENZE |
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Materiale a stampa |
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Livello bibliografico |
Monografia |
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3. |
Record Nr. |
UNINA9910809059703321 |
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Autore |
Schmiedel Jörn Matthias <1985-> |
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Titolo |
The role of microRNAs in controlling protein expression noise / / von Diplom Biophysiker Jörn Matthias Schmiedel |
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Berlin : , : Logos Verlag Berlin, , [2016] |
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©2016 |
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ISBN |
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Descrizione fisica |
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1 online resource (116 pages) : illustrations |
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Livello bibliografico |
Monografia |
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Note generali |
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PublicationDate: 20160331 |
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Nota di bibliografia |
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Includes bibliographical references (pages 103-114). |
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Sommario/riassunto |
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Long description: The expression of genes is based on stochastic processes, which lead to temporal fluctuations in the number of proteins of each gene. If such fluctuations become too large they can be detrimental to the fitness of an organisms, because most cellular processes are based on the precise interaction of proteins. This PhD thesis explores the role of post-transcriptional regulatory mechanisms in the control of stochasticity in gene expression, with a focus on microRNAs, common regulators in multicellular organisms. Bioinformatic data analysis, mathematical modeling and single cell expression experiments are used to analyze the conditions under which microRNAs can lead to the reduction of fluctuations in gene expression. The central insight of this thesis is that microRNAs can indeed reduce fluctuations for most genes and that they are likely used by organisms for this purpose, thus ensuring precision to gene expression during development and the maintenance of the adult body. Der Expression von Genen liegen stochastische Prozesse zu Grunde, die zu Fluktuationen in der Menge von Proteinen eines jeden Gens führen. Zu starke Fluktuationen in Proteinmengen können für Organismen schädlich sein, da die meisten zellulären Prozesse auf der präzisen Wechselwirkung von Proteinen beruhen. Diese Dissertationsschrift |
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befasst sich mit dem Einfluss von post-transkriptionellen Regulationsmechanismen auf die stochastischen Prozesse der Genexpression. Mittels bioinformatischer Datenanalyse, mathematischer Modellierung und gezielten Einzelzellexperimenten wird mit Fokus auf die in Mehrzellern weitverbreiteten microRNAs erforscht unter welchen Voraussetzungen Organismen post-transkriptionelle Regulation zu Verringerung von Fluktuationen benutzen können. Die zentrale Erkenntnis der vorliegenden Arbeit ist, dass microRNAs für die meisten Gene Fluktuationen verringern können und auch zu diesem Zweck genutzt werden. |
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4. |
Record Nr. |
UNINA9910847580503321 |
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Autore |
Huang Ken |
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Titolo |
Generative AI Security : Theories and Practices / / edited by Ken Huang, Yang Wang, Ben Goertzel, Yale Li, Sean Wright, Jyoti Ponnapalli |
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Pubbl/distr/stampa |
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Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 |
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Edizione |
[1st ed. 2024.] |
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Descrizione fisica |
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1 online resource (367 pages) |
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Collana |
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Future of Business and Finance, , 2662-2475 |
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Altri autori (Persone) |
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WangYang |
GoertzelBen |
LiYale |
WrightSean |
PonnapalliJyoti |
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Disciplina |
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Soggetti |
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Business information services |
Financial risk management |
Data protection |
Artificial intelligence |
Information technology - Moral and ethical aspects |
IT in Business |
Risk Management |
Data and Information Security |
Artificial Intelligence |
Information Ethics |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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Foundations of Generative AI -- Navigating the GenAI Security -- AI Regulations -- Build Your Security Program for GenAI -- GenAI Data Security -- GenAI Model Security -- GenAI Application Level Security -- From LLMOps to DevSecOps for GenAI -- Utilizing Prompt Engineering to Operationalize Cyber Security -- Use GenAI Tools to Boost Your Security Posture. |
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Sommario/riassunto |
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This book explores the revolutionary intersection of Generative AI (GenAI) and cybersecurity. It presents a comprehensive guide that intertwines theories and practices, aiming to equip cybersecurity professionals, CISOs, AI researchers, developers, architects and college students with an understanding of GenAI’s profound impacts on cybersecurity. The scope of the book ranges from the foundations of GenAI, including underlying principles, advanced architectures, and cutting-edge research, to specific aspects of GenAI security such as data security, model security, application-level security, and the emerging fields of LLMOps and DevSecOps. It explores AI regulations around the globe, ethical considerations, the threat landscape, and privacy preservation. Further, it assesses the transformative potential of GenAI in reshaping the cybersecurity landscape, the ethical implications of using advanced models, and the innovative strategies required to secure GenAI applications. Lastly, the book presents an in-depth analysis of the security challenges and potential solutions specific to GenAI, and a forward-looking view of how it can redefine cybersecurity practices. By addressing these topics, it provides answers to questions on how to secure GenAI applications, as well as vital support with understanding and navigating the complex and ever-evolving regulatory environments, and how to build a resilient GenAI security program. The book offers actionable insights and hands-on resources for anyone engaged in the rapidly evolving world of GenAI and cybersecurity. |
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